All posts tagged in paper .
Let’s talk about DINOv2, a paper that takes a major leap forward in the quest for general-purpose visual features in computer vision. Inspired by the success of large-scale self-supervised models in NLP (think GPTs and T5), the authors at Meta have built a visual foundation
DeepSeek-V2 introduces a major architectural innovation that enhances its efficiency as a language model – Multi-Headed Latent Attention (MLA). MLA stands out as a game-changing technique that significantly reduces memory overhead while maintaining strong performance. In this post, we will explore the fundamental concepts behind
Hey folks! I’m thrilled to share with you a research paper that I’ve been working on, diving deep into the fascinating realm of vision-based navigation for indoor robots. In my research paper titled “Real-time Vision-based Navigation for a Robot in an Indoor Environment”, I explore
Today we’re going to dive into a fascinating paper called “LOGIC-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning.” The authors of this paper claim that Large Language Models (LLMs) often struggle when faced with complex logical reasoning problems. Well, LLMs primarily
Sagar Manglani
manglanisagar@gmail.com
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I write articles on computer vision and robotics.
